code: def load_data():
      dataset = tf.keras.utils.get_file(
          fname="aclImdb.tar.gz",
          origin="http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz",  # noqa: E501
          extract=True,
      )
  
      # set path to dataset
      IMDB_DATADIR = os.path.join(os.path.dirname(dataset), "aclImdb")
  
      classes = ["pos", "neg"]
      train_data = load_files(
          os.path.join(IMDB_DATADIR, "train"),
          shuffle=True,
          categories=classes,
      )
      test_data = load_files(
          os.path.join(IMDB_DATADIR, "test"),
          shuffle=False,
          categories=classes,
      )
  
      x_train = np.array(train_data.data)
      y_train = np.array(train_data.target)
      x_test = np.array(test_data.data)
      y_test = np.array(test_data.target)
      return (x_train, y_train), (x_test, y_test)
  
file_path: autokeras/benchmark/experiments/text.py
imports: import os
  import numpy
  import tensorflow
  from sklearn.datasets import load_files
  import autokeras
  from benchmark.experiments import experiment
label_desc: Use image node_id 3 for calling the IMDB obj's underlying member method code with example usage: obj.load_data() and returns: x_train,  y_train,  x_test,  y_test